原后生动物论文活性污泥中常见原后生动物图像识别系统.docVIP

原后生动物论文：活性污泥中常见原后生动物图像识别系统【中文摘要】近年来,随着数字图像处理技术的发展,人们在数字图像处理技术的应用领域获得了喜人的成果。据文献记载,人们已经可以实现基于内容的图像检索以及对染色体图像的分类等等。论文设计与实现了一种活性污泥常见原后生动物图像识别的方法。对于一幅包含原后生动物和杂质的图片,首先要从中提取出原后生动物的主体,本文中介绍了两种提取方法,即全自动型目标提取算法与交互式目标提取算法。交互式目标提取是指输入一幅数字图像后,需要用鼠标标识出图像的目标与背景,而全自动目标提取方法则不需要。接着进行特征提取,本文从下面三个方面一共提取了16种特征：(1)形态特征,包括面积周长等,从这些特征中可以判断出这个原后生动物大致的形状,比如说类圆或类矩形等；(2)纹理特征,包括对比度、二阶矩等,从这些特征中可以得到这个原后生动物的表面结构组织排列信息以及它们与周围环境的联系；(3)其它特征,包括是否有尾巴、物体的均匀性等,从这些特征中可以得到这个原后生动物是否有尾巴以及它们的均匀情况。最后论文根据前面提取的特征,采用决策树的方法来进行分类。决策树算法的关键是给树的每个节点定义一个衡量标准。例如,在判断某个原后生动物的形状是否接近矩形时,可以用它的外接矩形与它自己本身的面积求商,如果这个值接近1表明它是接近矩形的。利用上述方法,论文针对活性污泥中常见的几种原后生动物,包括草覆虫、轮虫、线虫、豆虫、累枝虫和钟虫等进行了有效地识别。【英文摘要】In recent years, with the development of the digital image processing, applications of digital image processing technology have been received satisfactory results. According to historical records, content-based image retrieval system has been invented and chromosome images can be classified and so on.In this paper, we introduce an image recognition system for common protozoan and metazoan in activated sludge. For a picture containing protozoan, metazoan and impurities, first of all we have to extract the main body of the protozoan and metazoan, in this paper, we introduced two extraction methodsautomatic target extraction method and interactive target extraction method, interactive target extraction methods is after we enter a digital image, we need to use the mouse to identify the target and background, while we do not need to do it in automatic target extraction method. Then, feature extraction, in this paper, we extracted a total of 16 kinds of features according to the following three aspects:(1)Morphological characteristics, including area, perimeter, etc, from these features we can determine the approximate shape of the protozoan and metazoan. For example, round or rectangular, and so on. (2)Texture features, including contrast, second moment, etc, from these features, we can get the protozoan and metazoanssurface structure arrangement information and their links with the surrounding environment. (3)Other characteristics, including whether it has the tail, and its uniformity, etc. From these characteristics, we can know whether the protozoan and metazoan has the tail and its uniform situation. Finally, with the extracted features, we use Decision Tree approach to classification. Decision Tree algorithm is to focus on defining a measure to each node of the tree. For example, when we determine whether the protozoan and metazoanshape close to rectangular, we can use an external rectangular area divided by its own area of its own, and if this value is close to 1 indicates that it is close to rectangular. Detail steps will be described in the following article. Using the above methods, this paper focused on several common protozoan and metazoan in activated sludge, including paramecium, rotifer and nematode and so on, conducted effectively identify.【关键词】原后生动物 图像识别 目标提取 特征提取 分类【英文关键词】Protozoan and metazoan Image recognition Target detection Feature extraction Classification【目录】活性污泥中常见原后生动物图像识别系统摘要3-4Abstract4-5目录6-8第一章 绪论8-131.1 课题背景8-91.2 活性污泥常见原后生动物图像识别专家系统概述9-101.3 系统实现平台10-111.4 论文的主要研究内容和结构安排11-13第二章 全自动型目标提取13-282.1 基于边缘提取的算法14-202.1.1 图像预处理14-152.1.2 边缘检测15-162.1.3 膨胀处理162.1.4 内部填充16-192.1.5 平滑处理19-202.2 基于聚类的算法20-262.2.1 灰度化202.2.2 Gamma均衡20-232.2.3 中均值滤波232.2.4 二阶边缘增强232.2.5 双均值聚类23-242.2.6 形态学开运算242.2.7 最大独立成分检测24-262.3 两种算法的比较26-272.4 本章小结27-28第三章 交互式目标提取28-373.1 关于分水岭算法28-323.1.1 图像分割定义28-293.1.2 分割原理293.1.3 分水岭算法29-303.1.4 分水岭算法的改进30-323.2 分水岭算法在此系统中的实现32-363.2.1 分水岭算法函数323.2.2 鼠标事件有关函数32-343.2.3 实验结果34-363.3 本章小结36-37第四章 特征提取37-504.1 形态特征37-424.1.1 面积(area)37-384.1.2 周长(circumference)38-394.1.3 密集度(compact)和形态比(ratio)39-404.1.4 矩形度(rectangularity)和圆度(ellipticity)404.1.5 长宽比(ratio2)、长短轴比与方向()40-414.1.6 实验结果41-424.2 纹理特征42-444.2.1 灰度共生矩阵42-444.2.2 实验结果444.3 其它特征44-494.3.1 旋转45-464.3.2 是否有尾巴(whether_tail)46-474.3.3 对称性47-484.3.4 实验结